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Cargo Movements on Austria‘s Road Network (iMOVE)
EUROSTAT, Oct 11, 2012
Page 2
Austria‘s traffic model (current & future)
Used by the national & state authorities to plan infrastructure projects
Passenger & cargo induced road and rail traffic considering public as well as private transport
Forecast of volumes based on demographic projections, trade and production forecasts
A series of connected sub-models with a detailed network at its core to map actual and forecasted O/D flows
Actual O/D data essentially recompiled periodically (current version 2009)
Network characteristics
Overall 243.000 km (o. w. 109.000 road, 84.000 rail)
Austria 32.300 km (o. w. 26.000 road, 6.300 rail)
2412 counties/municipalities in Austria; 216 NUTS3 / NUTS0 regions in Europe
Page 3
Perceived weaknesses of the current approach
The model‘s empirical foundation
Insufficient accuracy of total transportation volume
Output of transportation sector 2004 estimates range between 363,5 and 415,8 mio. t/km depending on source
Underestimation by the European Road Freight Statistics ?
Inhomogeneous data collections Spatial differences (NUTS3, highway sections, counties)
Methodological differences between countries in collecting national road traffic data
Periodical differences (quarterly, yearly (t+1), every four years) between surveys
Laborious, expensive production process of base data
Main objectives of the iMOVE project
Combine & harmonize different surveys
Incorporate highway toll data into the O/D flows trips / between counties per truck category per day
Calibrate the O/D flows, using traffic count numbers of permanent counting stations
[Verify and consider the hypothesized growth in multimodal movements]
Prototype a repeatable data production process
Improve the production process and the quality of the O/D flow matrices
Page 5
Major data sources used to compile the O/D matrix
Austrian Road Freight Transport Statistics (SGVS) Sampling based on Austria‘s Vehicle Registry Political District Level Assumed underestimation (foreign (non EU) trucks/non-
response)
European Road Traffic Statistics (D-Tables) Only trucks registered nationally are surveyed, combined at
EU level Movements at NUTS3 level Assumed underestimation (foreign (non EU) trucks/non-
response)
Toll data records & Traffic counts Complete set of records collected at gantries for 2009
(highways) Traffic count data using automatic permanently installed
systems (primary & secondary roads)
Cross Alpine Freight Data (CAFT) All trucks, irrespective of nationality are surveyed Survey performed by Alpine nations every 4 years (O/D,
cargo) Performed at border crossings and major mountain passes
Planned production process
Calibration using the Network Model
Analyze and correct deviations
Valid annual O/D matrices
Traffic survey‘s
European Road Freight
Austrian RoadFreight
Statistics
Combine & disaggregate
Stage 1 O/D flows
Cross Alpine Freight
Toll Data Records
Traffic Count Data
Traffic counts
Stage 2 O/D flows
Map flows onto network graph
Page 7
Experiences, Status
Combining different survey‘s and traffic count information
Reconciling different value sets used in surveys to describe the same properties: Truck sizes, cargo types, goods classifications
Harmonizing, separating the use of different NUTS3 levels for origin and destination
Measuring the number of movements between two “traffic cells”
Derivation of journey’s from data collected at toll bridges
Disaggregating journeys from reported levels to „traffic cells“, using ecological inference approach.
Calibrating the route allocation of movements to road links
Minimizing deviations between calculated and counted traffic per link observing O/D movement bounds using non-linear optimization.
Backup
Page 8
Multilane free-flow system using micro wave technology
Page 9
Tolls collected if gross vehicle weight exceeds 3.5 tons
Rate groupCategory 2
2 axlesCategory 3
3 axlesCategory 4+
4 and more axlesA EURO emission classes EURO EEV & VI
0.146 0.2044 0.3066
B EURO emission classes EURO IV & V
0.156 0.2184 0.3276
C EURO emission classes EURO 0 to III
0.178 0.2492 0.3738Rates in EUR per kilometer driven (excl. 20 % VAT)
Usage dependent toll
Derivation of boundary conditions using toll information
Page 10
A&S-Netz
ASTn
ASTm
VZj
QZt
ASTl
VZk
QZs
VZi
Distribution of travel time between successive toll stations
Page 11
Type A Without rest areas / gas stations
Challenge: distribution of travel time …
Page 12
Type B With rest areas / gas stations
Challenge: distribution of travel time …
Page 13
Type CWith shopping centers/ business parks